Analysis / figures of results from h_DsRnn_Prep_spa.ipynb
Summarizing mult. RNNs / data sets based on Pandas ExTb and ProcTb.
PREC: h_DsRnnAna_Pd.iphnb
jupyter nbconvert --TemplateExporter.exclude_raw=True --TemplateExporter.exclude_input=True --to html --output tmp h_DsRnnAnaPd_Su1Vx7.ipynb
jupyter nbconvert h_DsRnnAnaPd_Su1Vx7.ipynb \
--to html \
--output tmp \
--TemplateExporter.exclude_raw=True \
--TemplateExporter.exclude_input=True \
--TagRemovePreprocessor.remove_cell_tags="{'rmCell'}" \
--TagRemovePreprocessor.remove_all_outputs_tags="{'rmOut'}" \
--RegexRemovePreprocessor.patterns="[r'(?ms).*DeprecationWarning.*']" \
--RegexRemovePreprocessor.patterns="[r'(?ms)Using TensorFlow.*']" \
Add this cell metadata (JSON) e.g: { "tags": ["rmOut"]}
Looks like Su 65 and 6 (or 78?) show the best results on these metrics.